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Paper Abstract and Keywords
Presentation 2025-12-05 15:40
Primary Bone Tumor Classification Based on Surgeon's Diagnostic Process
Takuya Miki, Koki Shimizu, Terumasa Aoki (TUT) MICT2025-50 MI2025-58
Abstract (in Japanese) (See Japanese page) 
(in English) Primary bone tumor is a rare disease, and it is difficult to diagnose. Also, diagnostic errors can give serious effects on patient outcomes. With the rapid advancement of AI technology, a lot of studies on AI diagnostic systems have been done for recent years. Unfortunately, most existing AI systems face some challenges. One of them is to generate input-data manually. Many of this work should be done by surgeons. It may cause an increase in surgeons’ work. Another challenge of them is that AI is difficult to focus on only lesion portions and to treat them well. In this paper, we present a novel diagnostic method for primary bone tumors, which is a two-stage classification approach using explainable AI (XAI). XAI simulates the diagnostic process of surgeons, that is, broadly overviewing the image first, after that focusing on doubtful regions. Our method visualizes diagnostic cues and estimates regions of interest by XAI at the first step. Next, it trains only the regions of interest. As the last step, it achieves three-class classification(no tumor, benign, malignant). Experimental results show that our method has a potent power to improve classification accuracy without increasing surgeons’ work.
Keyword (in Japanese) (See Japanese page) 
(in English) BTXRD / Radiograph / Bone Tumor / Osteosarcoma / XAI / DeepLearning / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 270, MI2025-58, pp. 74-77, Dec. 2025.
Paper # MI2025-58 
Date of Issue 2025-11-27 (MICT, MI) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF MICT2025-50 MI2025-58

Conference Information
Committee MICT MI  
Conference Date 2025-12-04 - 2025-12-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Okayama Convention Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical imaging technology, healthcare and medical information communication technology, etc. 
Paper Information
Registration To MI 
Conference Code 2025-12-MICT-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Primary Bone Tumor Classification Based on Surgeon's Diagnostic Process 
Sub Title (in English)  
Keyword(1) BTXRD  
Keyword(2) Radiograph  
Keyword(3) Bone Tumor  
Keyword(4) Osteosarcoma  
Keyword(5) XAI  
Keyword(6) DeepLearning  
Keyword(7)  
Keyword(8)  
1st Author's Name Takuya Miki  
1st Author's Affiliation Tokyo University of Technology (TUT)
2nd Author's Name Koki Shimizu  
2nd Author's Affiliation Tokyo University of Technology (TUT)
3rd Author's Name Terumasa Aoki  
3rd Author's Affiliation Tokyo University of Technology (TUT)
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Speaker Author-1 
Date Time 2025-12-05 15:40:00 
Presentation Time 20 minutes 
Registration for MI 
Paper # MICT2025-50, MI2025-58 
Volume (vol) vol.125 
Number (no) no.269(MICT), no.270(MI) 
Page pp.74-77 
#Pages 4 
Date of Issue 2025-11-27 (MICT, MI) 

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